class_docstr: A class that handles the parameters of Tensor Tracer.
docstr: Returns a map that contains the aggregate function for each signature.
docstr_tok: ["Returns","a","map","that","contains","the","aggregate","function","for","each","signature","."]
code: def get_signature_to_agg_fn_map(self):
      """Returns a map that contains the aggregate function for each signature."""
      # TODO(b/199284834): Aggregations are not accurate for mean and sparsity if
      # cores have a different number of elements. Variance uses the maximal core
      # variance.
      return {
          TRACE_MODE_NORM: linalg_ops.norm,
          TRACE_MODE_HISTORY: math_ops.reduce_max,
          TRACE_MODE_MAX_ABS: math_ops.reduce_max,
          TRACE_MODE_NAN_INF: math_ops.reduce_max,
          TT_SUMMARY_NORM: linalg_ops.norm,
          TT_SUMMARY_MAX: math_ops.reduce_max,
          TT_SUMMARY_MAX_ABS: lambda t, axis=0: math_ops.reduce_max(
              math_ops.abs(t),  # pylint: disable=g-long-lambda
              axis=axis,
          ),
          TT_SUMMARY_MIN: math_ops.reduce_min,
          # Exact if each part has the same number of values.
          TT_SUMMARY_SPARSITY: math_ops.reduce_mean,
          TT_SUMMARY_MEAN: math_ops.reduce_mean,
          TT_SUMMARY_VAR: math_ops.reduce_max,  # Simply reduce max variance.
          TT_SUMMARY_SIZE: math_ops.reduce_sum,
      }
  
imports: import os
  import os.path
  import re
  from absl import flags
  from tensorflow.python.ops import linalg_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.platform import tf_logging
label_desc: Use image node_id 13 for calling the TTParameters obj's underlying member method code with example usage: obj.get_signature_to_agg_fn_map() and returns: dict